1. Field of the Invention
This invention relates to a method and device for observing an object at a predetermined observation point, and more particularly to an improved traffic flow measuring device for observing vehicles on a road to measure data such as the number of passing vehicles, the speed of a vehicle and the types of vehicles (called as "traffic flow data" hereinafter) based on the time elapsing results of the measurement and to an improved parking lot observation device for observing vehicles parking in a parking lot.
2. Discussion of the Related Art
For the purpose of measuring traffic flow data, there has been heretofore developed a device in which a camera is installed above a road to take a picture at a predetermined position of the road and a flow of vehicles on the road is measured based on temporal changes of the taken pictures.
In this conventional device, a picture depicting no object on the road is stored as a background picture in advance, a difference between the picture from the camera and the stored background picture is extracted as a picture relating to vehicles, and the results of the extraction are sequentially processed to measure the flow of vehicles on the road (Japanese Electric Society Technical Report, Vol. 512, pp. 80-81).
There also has been proposed a measuring method in which instead of the advance storage of such a background picture, a previously taken picture is stored to subtract the stored previous picture from the latest taken picture to extract only the change of the position of the vehicle.
Quite recently, there has been proposed technique (DTT method) for measuring traffic flow data by making space-time pictures accumulated about pictures taken by a camera for each time (Japanese Electronic Information Communication Society Journal, Vol. J77-D-11 No. 10, pp. 2019-2026, 1994). According to this method, characteristic quantity data such as outline of a vehicle is extracted from the pictures every predetermined time, and the extracted characteristic quantity data is projected on a direction axis in parallel with a movement direction of a vehicle to provide one dimension data. This one dimension data is further arranged in time series to provide a two dimension picture (DDT picture) consisting of a direction axis and a time axis, and the DDT picture extracts an object moving in a predetermined direction.
In order to discriminate whether or not each parking area of a parking lot is vacancy, the above-mentioned first or second method is employed. In other words, the inquiry whether or not a vehicle is parked at a parking area is performed based on the difference between the input picture and the background picture which are obtained by taking a picture at an observation position or the difference between the input picture and its just before taken picture.
When the difference between the input and the background pictures is employed to measure a traffic flow, it is necessary to store background pictures corresponding to various circumstances, such as day and night, fine and rain or the like. In this case, assumption of necessary circumstances or revision of background pictures according to the change of circumstances is limited, and extraction of vehicles with high precision is impossible. The above-mentioned first, second and third methods have the disadvantage that they erroneously detect other movement than vehicles as a vehicle, such as the shadow of a vehicle, the shadow of a tree swaying by a wind, other shadow moving on the road, the reflection from a light in the night, the vehicle reflected in the wet road surface, or the like.
When a large size vehicle exists on a road or traffic congestion happens, the conventional methods have the disadvantages that each vehicle cannot be precisely discriminated, and a plurality of vehicles are erroneously detected as a single vehicle. When a picture of the shadow of a large size vehicle reaches its neighbor lane to overlap a small size vehicle behind the large size vehicle, the small size vehicle is erroneously detected as a large size vehicle. Thus, the number and types of the vehicles on the road cannot be precisely discriminated. These problems are applicable to a conventional observation device at a parking lot, such as decrease of a discriminating accuracy by change of illuminance at an observation point, and erroneous detection of the shadow of a vehicle in neighbor area.
The conventional methods need a storage for storing various background pictures and a picture for each time period, and a hardware for operations such as subtraction and cumulative addition about each picture, so that a whole construction of the conventional device is an a large scale and its manufacturing cost is high.